Presentation on theme: "INTERNATIONAL INSTITUTE FOR GEO-INFORMATION SCIENCE AND EARTH OBSERVATION Simulating informal settlements growth in Dar es Salaam, Tanzania; a hierarchical."— Presentation transcript:
INTERNATIONAL INSTITUTE FOR GEO-INFORMATION SCIENCE AND EARTH OBSERVATION Simulating informal settlements growth in Dar es Salaam, Tanzania; a hierarchical framework Ellen-Wien Augustijn, Johannes Flacke and Asif Iqbal ICA Workshop 2009 Gävle, Sweden
Factors leading to development and growth of informal settlements weakness of the statutory planning process strong rural-urban migration leading Leading to: Enormous population growth Other contributing factors: problems with land tenure lack of formal surveyed building plots poor land administration systems
Prevailing urban trends in developing countries: Growth of informal settlement (ISG) approx. 80 % of urban growth in developing countries is “informal” Informal settlements are densely populated urban residential areas with informal or insecure land tenure inadequate access to basic services no planning and no building permissions not necessarily slums global phenomenon (for LDC), varying pattern
Informal settlement process differs from a formal settlement process A limited number of simulation models were developed for informal settlements No body of theory exists for the development of IS in developing countries, simulation models can contribute to a better understanding of the process and theory development.
ISG in Dar es Salaam, Tanzania 70 % of growth in informal majority of the settlers buy/inherit the land accommodates a wide variety of social groups of different income level Densities are low in the beginning and increase over time Development of vacant or agricultural land
ISG in Dar es Salaam, Tanzania 1.Initial settlement on peripheral land 2.Simple low cost houses 3.Consolidation with own improvements 4.Beginning of room rental market 5.Government involvement (upgrading) 6.Increase in absentee owners 7.Continual improvements, gentrification
Relating IS to hierarchy theory complex systems have two lines of organization, a vertical structure and a horizontal structure. The vertical structure is composed of levels and the horizontal structure of sub models (Wu and David, 2002). Each hierarchical level has a particular rate of processes where higher levels have a slower process and lower levels have a faster Land use change is generally seen as a multi-scale process in which processes - driving factors operate at different scales Besides the individual settler, other actors are actively responsible for the growth and change in informal settlements. These actors include the local government. (vertical structure) Horizontally three subsystems can be identified Hierarchy theoryInformal Settlements
Factors influencing ISG - sub models ISG Economic factors Cultural factors Physical factors Social contacts Family ties traditional systems Gentrification Commercial Room rental Land quality Land prices Accessibility Upgraded utilities
Objective The objective of this study is to create a two level hierarchical model consisting of: a city wide settlement model a micro-level housing model
Conceptual framework City level or settlement model Housing Model
Driving factors LandscapeEconomicSocial Higher level “settlement model” Accessibility: -Main roads -Railway Closeness to: -CBD -River -Formal settlement Neighborhood Density of the urban area Price of landSocio-economic status of the area NeighborhoodAvailability of farmland Lower level “Housing” model Risks: -Slope -flood area Price of a parcelMarket place Transportation: -Road -Bus stop TenantsChurch Water: -river -water distribution points Family – tribe ties
Conceptual framework Settlement model Raster based Temporal resolution – year Actors include government Growth of settlements, new roads, upgrading from informal to formal Housing model Vector based Temporal resolution – day to month Actor is the family Choice of plot, building of houses, renting of rooms
Implementation of the housing model a.Movement of Agents New Agents are created at a random location Agent will move to the closest house Movement from centroid to centroid agent will select a new house within its search radius b.Settlement Behavior c.Cross-Layer Feedbacks
Implementation of the housing model a.Movement of Agents b.Settlement Behavior new houses are built next to existing houses The space required varies per type of building When sufficient space is available the agent will check cost factors and attractiveness of the location calculating the suitability c.Cross-Layer Feedbacks Road
Implementation of the housing model a.Movement of Agents b.Settlement Behavior New house Extension of an existing house Only small or medium size houses can be extended small houses will always be situated between the existing house and the road c.Cross-Layer Feedbacks
Results Test runs were conducted for the time period 1987 to 1992 for Manzese settlement Agents have preferences related to distance to roads and footpaths (roads being preferred above footpaths), and an avoidance behavior in relation to the flood risk areas. Agents belong to different income groups and are either tenants or house owners. Existing buildings (as polygons), infrastructure and the flood zone are used as input.
Results Flood zone Existing houses Foot path Road Simulated house
Discussion Aim of the project described here is to develop a two-layer hierarchical model containing an economic model, a social model and a landscape model. Only one layer of this model (the micro housing level) has been implemented so far Improvements on the housing model Development of the city level model
Limitations of the existing housing model The current model is only suitable for modeling the densification process not for new spontaneous growth. Of the social aspects only the difference between owners and tenants is implemented. This aspect can be further extended. Currently the model only contains the roads, footpaths and flood zone area as physical features. This should be extended to include the slope, water distribution points, and possibly the access to utility infrastructure. There is no mechanism of selling houses, so agents that settle in the area will not leave; this is an unrealistic limitation of the model.
Validation of the housing model the predictive accuracy (correlation with actual data) Extensive data are available Tests can be conducted on other informal settlements and different time periods process accuracy Difficult although some processes are documented